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Index Performance and talent management Skills intelligence › Lightcast Open Skills vs Fuel50
Skills intelligence · September 2026 Edition

Lightcast Open Skills vs Fuel50

Zero of twelve models named Lightcast Open Skills first on the direct prompt; one named Fuel50. Lightcast Open Skills was named by ten of the twelve models and Fuel50 by seven and both carry 12 labels, so the shares below are directly comparable.

Lightcast Open Skills

accepted challenger

Named in one category this edition.

Fuel50

accepted challenger

Named in six categories this edition.

First-choice share9%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 16; printed, not drawn.
Labels1212Equal, which is what makes the shares comparable.
The two percentage rows are drawn on one 0 to 100 track, Lightcast Open Skills reading right to left. Rank and label count are printed, not drawn.TalentGuard was named alongside these two in nine of the twelve direct answers. TalentGuard vs Lightcast Open Skills · TalentGuard vs Fuel50 · Skills Base vs Lightcast Open Skills

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the skills intelligence page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Lightcast Open SkillsFirst choices, of twelve modelsFuel50
Direct01
Paraphrase40
Comparative01
Budget-constrained001 against Lightcast Open Skills · 1 against Fuel50
Scale-constrained00
Negative00
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Lightcast Open Skills and Fuel50 stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Lightcast Open Skills Fuel50 first choice named as an alternative argued againstblank: not namedEach cell is one answer, Lightcast Open Skills on the left and Fuel50 on the right.

The direct prompt

The plain question, one answer per model, grouped by where Lightcast Open Skills and Fuel50 stood in it.

Fuel50 first, Lightcast Open Skills not the choice

1 of 12 modelsLightcast Open Skills was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashFuel50, TalentGuard alternatives: MuchSkills, Skills Base

Neither was the first choice, one was named

5 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniEightfold AI, SkillPanel alternatives: Fuel50, Retrain.ai, Workday Skills Cloud
Gemini 3.5 FlashCareer Bird alternatives: Docebo, Fuel50, Workera
Grok 4.1 FastTalentGuard, iMocha alternatives: Fuel50
Qwen 3.7 FlashEightfold AI alternatives: Clad.io, DeepSkill, Gloat, Lightcast Open Skills
Kimi K2TalentGuard alternatives: 365Talents, Engagedly, Fuel50, TechWolf

Neither was named

6 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5TalentGuard alternatives: Amplemarket, iMocha
Perplexity SonarTalentGuard alternatives: INOP, SkillPanel, Skills Base, iMocha
Mistral SmallTalentGuard, iMocha alternatives: Bryq, INOP
Llama 4 MaverickTalentGuard alternatives: Criteria Corp, Engagedly, iMocha
GLM 4.7 FlashXiMocha alternatives: MuchSkills, Skills Base, TalentGuard
MiniMax M2.5TalentGuard alternatives: 365Talents, Gloat

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Lightcast Open Skills leads by twelve points.
Lightcast Open Skills12%#– of 10
Fuel500%#– of 10
The full small business standing →
Mid-marketThe figures above
Lightcast Open Skills leads by six points.
Lightcast Open Skills9%#4 of 16
Fuel502%#8 of 16
The full mid-market standing →
Enterprise
Lightcast Open Skills leads by five points.
Lightcast Open Skills9%#4 of 10
Fuel505%#6 of 10
The full enterprise standing →

What the models said about Lightcast Open Skills

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“Enterprise platforms like ... Lightcast, etc. tend to be stronger but usually not the best fit for a tight budget.” GPT-5.4 mini · budget prompt · soft negative
“The Industry Standard: Lightcast Skills Taxonomy (formerly Emsi Burning Glass)... The absolute gold standard in labor market data.” Gemini 3.5 Flash · paraphrase prompt · first choice
“I'd recommend Lightcast Open Skills as the skills taxonomy paired with TechWolf as the inference tool” Grok 4.1 Fast · paraphrase prompt · first choice
“I'd usually recommend Lightcast Skills Taxonomy + a Lightcast-based inference layer as the default choice” GPT-5.4 mini · paraphrase prompt · first choice

What the models said about Fuel50

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“Best overall for enterprise — maps employee skills, career paths, and internal mobility, with gap analysis tied to learning evidence.” DeepSeek V4 Flash · comparative prompt · first choice
“I'd shortlist TalentGuard ... and Fuel50 (if you want higher-fidelity skills intelligence with proven inference)” DeepSeek V4 Flash · direct prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.